Sammanfattning

We created an AI support for diagnosis in dyspneic adults at time of triage in the emergency department.

Complete data from an entire regional health care system was analyzed, to find AI-derived, unknown, important diagnostic predictors. Most important were prior diagnoses of heart failure or COPD, daily smoking, atrial fibrillation/flutter, life difficulties and maternal care.

Sensitivity for AHF, eCOPD and pneumonia was 75%, 93%, and 54%, respectively, with a specificity above 75%.

Each patient visit received an individual graph with the AI´s underlying decision basis.
Originalspråkengelska
StatusPublished - 2023 sep.
EvenemangEuropean Emergency Medicine Congress 2023 - Barcelona, Spanien
Varaktighet: 2023 sep. 172023 sep. 20

Konferens

KonferensEuropean Emergency Medicine Congress 2023
Land/TerritoriumSpanien
OrtBarcelona
Period2023/09/172023/09/20

Ämnesklassifikation (UKÄ)

  • Kardiologi

Fria nyckelord

  • Artificiell intelligens
  • AI
  • Dyspne

Fingeravtryck

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